David Brin, Astrophysicist
One of the biggest problems with traditional armour has been that it is extremely heavy, even for occasional use in cars. It can’t be used on vehicles that don’t have significantly powerful engines as the added weight of steel makes the vehicle too heavy to be driven at regular speeds. David Brin tweeted about Composite Metal Foams (CMFs) that North Carolina State University professor Afsaneh Rabiei has spent the last few years developing. It’s a new material that is tough enough to turn an armour-piercing bullet into dust. This means that CMF plating doesn’t just stop a bullet from piercing through, it actually shatters it. “We could stop the bullet at a total thickness of less than an inch, while the indentation on the back was less than 8 millimetres,” Rabiei says. On traditional steel armour, the US National Institute of Justice makes it mandatory that there be at least 44 mm of steelplating in order to stop armour-piercing bullets. The material also has similar elasticity to bone, so it could be used for making a new generation of biomedical implants that would avoid bone rejection, something that often results from implant materials like titanium.
Vaughan Bell, Neuroscientist
When a two or three-year-old goes to the zoo and sees an elephant for the first time, they are quick to identify it as the massive creature from the drawing they have seen in their books. Though it may seem like a simple task, it is, in fact, one of the facets of the human brain that makes it so unique. Which is why researchers have been trying for decades to replicate the “time of visual identification” in computers, according to an article tweeted by Vaughan Bell. We are also much better at learning on our own (how a toddler learns about gravity after falling down a few times), solving unstructured problems and finding relevant data in floods of information. “Humans are much, much better generalists,” said Tai Sing Lee, a computer scientist and neuroscientist at Carnegie Mellon University in Pittsburgh. To overcome this gap, the US government has started funding a massive project to bring artificial intelligence more in line with our own mental powers. Three teams have been assigned to map and model a chunk of the human brain in unprecedented detail. “We want to revolutionise machine learning by reverse engineering the algorithms and computations of the brain,” Jocab Vogelstein, chief of Intelligence Advanced Research Projects Activity (IARPA) said. By the end of the five-year IARPA project, researchers aim to map a cubic millimetre of cortex. No one has ever managed to map the brain at this scale. Once mapped, specialised algorithms will be prepared that have visual processing so that it can identify objects from drawings or rough illustrations, much like a toddler in a zoo does.